Classical machine learning and statistics datasets from
the UCI Machine Learning Repository and other sources.

The datasets package defines two different kinds of datasets:

small data sets which are directly (or indirectly with file-embed)
embedded in the package as pure values and do not require network or IO to download
the data set. This includes Iris, Anscombe and OldFaithful.

other data sets which need to be fetched over the network with
Numeric.Datasets.getDataset and are cached in a local temporary directory.

The datafiles/ directory of this package includes copies of a few famous datasets, such as Titanic, Nightingale and Michelson.

Changes

0.4
* Get rid of dependency on ‘data-default’ (introduced by previous versions of ‘req’)

* Bump 'req' dependency to 2.0.0

0.3
* ‘datasets’ hosted within the DataHaskell/dh-core project

* use 'req' for HTTP and HTTPS requests, instead of 'wreq'
* Mushroom and Titanic datasets
* Restructured top-level documentation
* Removed 'csvDatasetPreprocess' and added 'withPreprocess'. Now bytestring preprocessing is more compositional, i.e. 'withPreprocess' can be used with JSON datasets as well.